Characterization of the proteome of organelles and subcellular domains is essential for understanding cellular organization and identifying protein complexes as well as networks of protein interactions. We established a proteomic mapping platform in live Drosophila tissues using an engineered ascorbate peroxidase (APEX). Upon activation, the APEX enzyme catalyzes the biotinylation of neighboring endogenous proteins that can then be isolated and identified by mass spectrometry. We demonstrate that APEX labeling functions effectively in multiple fly tissues for different subcellular compartments and maps the mitochondrial matrix proteome of Drosophila muscle to demonstrate the power of APEX for characterizing subcellular proteomes in live cells. Further, we generate “MitoMax,” a database that provides an inventory of Drosophila mitochondrial proteins with subcompartmental annotation. Altogether, APEX labeling in live Drosophila tissues provides an opportunity to characterize the organelle proteome of specific cell types in different physiological conditions.

Understanding the quantitative implications of P-glycoprotein and breast cancer resistance protein efflux is a key hurdle in the design of effective, centrally acting or centrally restricted therapeutics. Previously, a comprehensive physiologically based pharmacokinetic model was developed to describe the in vivo unbound brain-to-plasma concentration ratio as a function of efflux activity measured in vitro. In the present work, the predictive utility of this framework was examined through application to in vitro and in vivo data generated on 133 unique compounds across three preclinical species. Two approaches were examined for the scaling of efflux activity to in vivo, namely relative expression as determined by independent proteomics measurements and relative activity as determined via fitting the in vivo neuropharmacokinetic data. The results with both approaches indicate that in vitro efflux data can be used to accurately predict the degree of brain penetration across species within the context of the proposed physiologically based pharmacokinetic framework.

The high density lipoprotein (HDL) receptor, scavenger receptor class B, type I (SR-BI), binds HDL and mediates selective cholesteryl ester uptake. SR-BI's structure and mechanism are poorly understood. We used mass spectrometry to assign the two disulfide bonds in SR-BI that connect cysteines within the conserved Cys321-Pro322-Cys323 (CPC) motif and connect Cys280 to Cys334. We used site-specific mutagenesis to evaluate the contributions of the CPC motif and the side chain of extracellular Cys384 to HDL binding and lipid uptake. The effects of CPC mutations on activity were context dependent. Full wild-type (WT) activity required Pro322 and Cys323 only when Cys321 was present. Reduced intrinsic activities were observed for CXC and CPX, but not XXC, XPX or XXX mutants (X≠WT residue). Apparently, a free thiol side chain at position 321 that cannot form an intra-CPC disulfide bond with Cys323 is deleterious, perhaps because of aberrant disulfide bond formation. Pro322 may stabilize an otherwise strained CPC disulfide bond, thus supporting WT activity, but this disulfide bond is not absolutely required for activity. C384X (X=S,T,L,Y,G,A) mutants exhibited altered activities that varied with the side chain's size: larger side chains phenocopied WT SR-BI treated with its thiosemicarbazone inhibitor BLT-1 (increased binding, decreased uptake); smaller side chains produced almost inverse effects (increased uptake:binding ratio). C384X mutants were BLT-1 resistant, supporting the proposal that Cys384's thiol interacts with BLT-1. We discuss the implications of our findings on the functions of the extracellular loop cysteines in SR-BI and compare our results to those presented by other laboratories.

No abstract

The use of in vitro cell culture model systems has revealed many potential mediators and candidate biomarkers of various disease phenotypes. To be of clinical utility, the expression of these candidates must be assessed in patient samples such as tissue, urine or blood. However, typical "omic" experiments may produce candidates in such large numbers that it is usually impossible to test all of these in clinical samples. Here, we present a proteomic approach to discover and prioritize candidate biomarkers that are more likely to be found in serum. Using a combination of experimental and in silico approaches, we have demonstrated this approach using an isogenic cell culture model of breast cancer invasion. Differential proteomics (2D-DIGE) was used to discover a number of candidate biomarkers and a subset of these were identified as "extracellular". We tested the validity of this approach by screening serum from breast cancer patients for these candidates and then verified the presence of several of these "extracellular" proteins. This approach provides a pragmatic approach to prioritizing candidates that may be most suitable for downstream assays such as multiple reaction monitoring.